1. Field
The following description relates to a method and an apparatus to classify data and segmenting region of interests (ROI), and more particularly, to a method and an apparatus using a hypothesis to classify data and segmenting the ROI on a basis of a gradient.
2. Description of the Related Art
Generally, an object is detected from given data through machine learning so as to classify to which class the detected object belongs. In one example, for the general machine learning method to classify data, there are the following representative methods: neural networks, convolutional neural networks (CNNs), support vector machines (SVMs), logistic regression, and nearest neighbors. Also, for a general method to detect data, specified methods according to data types exist. For example, a method to detect image data includes scale-invariant feature transform (SIFT), deformable part model (DPM). A method to detect audio data includes a recurrent neural network (RNN).
Above this, the various methods for detecting and classifying an object from data enunciated above perform tests on every available position of data, thereby causing an increase in test duration and a reduction in detection accuracy.